The present invention relates to methods and apparatus for producing a time variant asset allocation among a plurality of investments and, more particularly, to producing an allocation equation that may be utilized to predict a substantially optimal allocation of assets among the investments at one or more points in time.
It is desirable to determine an optimal allocation of assets among a plurality of investments (i.e., an investment portfolio). For example, an investor may wish to distribute his assets among investments A, B, and C. The investor's return on the portfolio will depend on the respective market values of investments A, B, and C, as well as the distribution of his assets by percentage among these investments (i.e., the allocation of his assets). It is self evident that the investor would like to maximize his return on the investment portfolio by selecting an advantageous allocation of assets among the investments.
In keeping with the desire to maximize the return on an investment portfolio, those skilled in the art have sought to develop procedures for determining an advantageous allocation of assets among a plurality of investments. For example, the so-called Markowitz model was developed in the early 1950s to compute a desirable allocation of assets among a plurality of investments based on historical relationships among the investments. More particularly, the Markowitz model is frequently implemented by requiring that the average returns of the respective investments and the standard deviations of those returns are computed for a particular historical period. A correlation matrix is then determined, which defines the extent to which the investments are linked (i.e., correlated) in terms of their market values over the historical period. The Markowitz model then uses a quadratic programming routine to compute an asset allocation among the investments that minimizes the square of the standard deviation of the returns of the investment portfolio. Inputs to the quadratic programming routine include a desired average return (for the investment portfolio set by the investor), the average returns for each investment, the standard deviations of these returns, and the correlation matrix. The resultant asset allocation is fixed as a function of time.
Unfortunately, the asset allocation obtained via the Markowitz model has significant drawbacks. For example, the Markowitz asset allocation does not provide an asset allocation that is time variant. Consequently, the investor must either use a fixed asset allocation and hope for the best over time, or recompute the average rates of return for each investment, the standard deviation of these returns, and the correlation matrix to determine a new asset allocation for a new time period. The new asset allocation, however, would be heavily skewed by the historical average of the returns of each investment and, therefore, would not provide satisfactory asset allocations, particularly for short term distributions (e.g., monthly, weekly, daily, etc.).
Further disadvantages of the Markowitz model include that it does not permit other market factors to affect the asset allocation and, therefore, the computed asset allocation cannot be influenced by, for example, leading market indicators. By way of example, many investments may be affected by inflation rates and, thus, it would be beneficial to adjust asset allocations based on them. Since the Markowitz model relies heavily on the historic performance of the portfolio investments (e.g., the average return), the Markowitz model has no mechanism for directly adjusting the asset allocation based on changes in current inflation rates. This could result in highly undesirable asset allocations when there is a significant disparity between average and current inflation rates over a relevant historical period. For example, a particular inflation rate may have averaged ten percent during the relevant historical period, but the current inflation rate may be three percent. The Markowitz model, however, would at best yield an asset allocation corresponding to the ten percent level.
Another model was developed by Konno and Yamazaki in the early 1990s to compute asset allocations among a plurality of investments. In their process, the historical monthly returns for each investment of the portfolio are used in a linear programming routine to minimize a sum of differences between the rates of return of the investments and an minimum desired rate of return. Like the Markowitz model, the Konno and Yamazaki model yields an asset allocation that is time invariant. Thus, the asset allocation computed by the Konno and Yamazaki model represents an average allocation for use in long term investing. The Konno and Yamazaki model is not equipped to provide an investor with the information needed to make short term asset allocation changes, such as monthly, weekly, daily, etc.
Accordingly, there is need in the art for new methods and apparatus for determining time variant asset allocations among a plurality of investments based, among other things, on market factors such that the investor can quickly respond to changing market conditions.